Statistical Inference of Weibull Extension Distribution under Imprecise Data

Authors

M. Seham, Department of Mathematics, Faculty of Science, Aswan University, Aswan, Egypt\\ Academy of Scientific Research and Techonolgy(ASRT), EgyptFollow
M. Amira Younis, Department of Mathematics, Faculty of Science, Aswan University, Aswan, Egypt\\ Academy of Scientific Research and Techonolgy(ASRT), EgyptFollow

Abstract

In this paper, we present the maximum likelihood (ML) and Bayes estimation of the unknown parameters, the reliability and hazard functions of the Weibull extension distribution based on progressively Type-II censoring scheme from fuzzy lifetime data. For the computation of Bayes estimates, we proposed using Tierney-Kadane’s approximation under square error and LINEX loss functions. The performance of the maximum likelihood and Bayes estimators compared in terms of their mean squared errors (MSEs) through the simulation study. The results indicated that MSEs based on Tierney-Kadane’s approximation are less than based on the ML method. Finally, to demonstrate the efficiency of the proposed methods, two real data sets are analyzed.

Recommended Citation

Seham, M. and Amira Younis, M. (2022) "Statistical Inference of Weibull Extension Distribution under Imprecise Data," Information Sciences Letters: Vol. 11 : Iss. 3 , PP -.
Available at: https://digitalcommons.aaru.edu.jo/isl/vol11/iss3/3